Abstract:
BACKGROUND:Mouse xenografts from (patient-derived) tumors (PDX) or tumor cell lines are widely used as models to study various biological and preclinical aspects of cancer. However, analyses of their RNA and DNA profiles are challenging, because they comprise reads not only from the grafted human cancer but also from the murine host. The reads of murine origin result in false positives in mutation analysis of DNA samples and obscure gene expression levels when sequencing RNA. However, currently available algorithms are limited and improvements in accuracy and ease of use are necessary. RESULTS:We developed the R-package XenofilteR, which separates mouse from human sequence reads based on the edit-distance between a sequence read and reference genome. To assess the accuracy of XenofilteR, we generated sequence data by in silico mixing of mouse and human DNA sequence data. These analyses revealed that XenofilteR removes > 99.9% of sequence reads of mouse origin while retaining human sequences. This allowed for mutation analysis of xenograft samples with accurate variant allele frequencies, and retrieved all non-synonymous somatic tumor mutations. CONCLUSIONS:XenofilteR accurately dissects RNA and DNA sequences from mouse and human origin, thereby outperforming currently available tools. XenofilteR is open source and available at https://github.com/PeeperLab/XenofilteR .
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Kluin RJC,Kemper K,Kuilman T,de Ruiter JR,Iyer V,Forment JV,Cornelissen-Steijger P,de Rink I,Ter Brugge P,Song JY,Klarenbeek S,McDermott U,Jonkers J,Velds A,Adams DJ,Peeper DS,Krijgsman Odoi
10.1186/s12859-018-2353-5subject
Has Abstractpub_date
2018-10-04 00:00:00pages
366issue
1issn
1471-2105pii
10.1186/s12859-018-2353-5journal_volume
19pub_type
杂志文章abstract:BACKGROUND:Biclustering has been largely applied for the unsupervised analysis of biological data, being recognised today as a key technique to discover putative modules in both expression data (subsets of genes correlated in subsets of conditions) and network data (groups of coherently interconnected biological entiti...
journal_title:BMC bioinformatics
pub_type: 杂志文章
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abstract:BACKGROUND:During the last few years, DNA sequence analysis has become one of the primary means of taxonomic identification of species, particularly so for species that are minute or otherwise lack distinct, readily obtainable morphological characters. Although the number of sequences available for comparison in public...
journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2005-07-18 00:00:00
abstract:BACKGROUND:Although many genomic features have been used in the prediction of protein-protein interactions (PPIs), frequently only one is used in a computational method. After realizing the limited power in the prediction using only one genomic feature, investigators are now moving toward integration. So far, there hav...
journal_title:BMC bioinformatics
pub_type: 杂志文章
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journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2013-06-22 00:00:00
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journal_title:BMC bioinformatics
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更新日期:2015-02-20 00:00:00
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journal_title:BMC bioinformatics
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更新日期:2018-10-01 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2018-09-04 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章,已发布勘误
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更新日期:2020-01-22 00:00:00
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更新日期:2010-06-15 00:00:00
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pub_type: 杂志文章
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更新日期:2005-05-31 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2019-12-30 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章
doi:10.1186/s12859-015-0847-y
更新日期:2016-01-11 00:00:00
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journal_title:BMC bioinformatics
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更新日期:2018-07-18 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2013-03-27 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2004-12-17 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2017-12-28 00:00:00
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pub_type: 杂志文章
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更新日期:2019-04-03 00:00:00
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更新日期:2019-04-25 00:00:00
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pub_type: 杂志文章
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更新日期:2006-09-06 00:00:00
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更新日期:2010-01-18 00:00:00
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更新日期:2010-07-23 00:00:00
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更新日期:2010-02-25 00:00:00
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更新日期:2004-08-14 00:00:00
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